twoarm_sim: Simulates data from a two-arm parallel cluster randomised...

In crctStepdown: Univariate Analysis of Cluster Trials with Multiple Outcomes

Simulates data from a two-arm parallel cluster randomised trial

Description

Simple simulation of two Poisson distributed outcomes for a two-arm parallel cluster randomised trial with no baseline measures. A log-linear model is specified y~Poisson(lambda) with lambda = exp(mu + beta*D + theta) where D is the treatment effect indicator equal to one in clusters with the treatment and zero otherwise, and theta~N(0,sigma^2) is the cluster random effect. Used for testing error rates of the methods.

Usage

twoarm_sim(
  nJ = c(7, 7),
  N = 20,
  mu = rep(1, 2),
  beta = c(0, 0),
  sig_cl = rep(0.05, 2)
)

Arguments

nJ	Vector of two integers with the number of clusters in treatment and control arms
N	Number of individuals per cluster
mu	Vector of two numeric values with the intercept terms for the two models on the log scale
beta	Vector of two numeric values that are the treatment effect parameters in the two models
sig_cl	Vector of two values equal to the variance of the random effect in each model

Value

A list consisting of: (1) data frame with the cluster IDs (cl), treatment effect indicators (treat), and two outcomes (y1, y2), and (2) the values of the treatment effect parameters used in the simulation.

Examples

out <- twoarm_sim()
data <- out[[1]]

crctStepdown documentation built on May 29, 2024, 2:48 a.m.